Methodology for modeling the impact of traffic burstiness on high-speed networks

Recent results published by Leland, Taqqu, Willinger and Wilson (1994), Addie, Zukerman and Neame (see IEEE Communications Magazine, p.88-95, 1998), and by Taqqu, Teverovsky and Willinger (1995) prove that high-speed network traffic is more bursty and its variability cannot be predicted as assumed previously. According to the authors, network traffic has similar statistical properties in a certain amount of time called self-similarity. One of the consequences is that combining the various flows of data, as it happens for example in ATM virtual paths, does not result in the smoothing of traffic. Combining bursty data streams will also produce bursty combined data flow. The studies imply that the methods and models used in traditional network design require modifications. This paper presents a new methodology that estimates and measures the impact of bursty traffic on network links and network devices applying discrete event simulation techniques. By using the new methodology, we can get more accurate results in measuring the momentarily utilization of links, response time, and the queuing performance of switches and routers in a large network. We illustrate the methodology with a Comnet model